Family offices ask us constantly: “How are you using AI?” In fintech, where a single misclassified transaction can cascade into tax problems, this question demands a specific answer, not platitudes about innovation.
We know that we have to strike a careful balance between automation, which makes our lives easier, and human oversight, which requires labor hours. At the same time, our approach leverages innovation with today’s powerful technologies without compromising on the precision, privacy, and security our clients need from our product.
Overall, our approach to AI is to enhance the accuracy and efficiency of every workflow it touches, without compromising on the pillars of trust and confidentiality that are so important to family offices. With that, our philosophy is to deploy AI only where it demonstrably improves outcomes.
The evolving role of AI in the family office
Software used by family offices is not typically built with the needs of family offices in mind. Take accounting software, for example; QuickBooks is made for the small business owner that may not have an accounting background, and Sage is made for larger operating companies with multiple legal entities.
With AI tools becoming widely available, the barrier to entry for new technologies is lower than ever. With that, the market will likely see consolidation among technology providers — especially as it becomes easier for companies to develop products that fit horizontally into their suite of offerings.
However, family offices shouldn’t chase trends. Yes, expectations have evolved — and family office professionals now expect AI to be part of the toolkit — but AI needs to work with you, not just for you.
For us at SumIt, that expectation reinforces a truth that we bring to work every day: AI is here to enhance human judgment and aid in accuracy and efficiency. And that belief is at the heart of how we build and apply technology.
Our approach: Crawl, walk, run
We like to describe our approach to AI as the “crawl, walk, run” method. We start small — by crawling — and apply AI only to workflows that are well-defined and clearly understood. That way, it’s easy for us to identify if part of the process gets derailed or if information is compromised.
For example, take a transaction that comes in from a bank feed and needs to be categorized into a general ledger. That’s a process with predictable inputs and outcomes, which is exactly the kind of workflow that benefits from automation. When we know what the data looks like and what the desired result should be, we can safely and effectively layer AI on top of it. Humans can periodically check to make sure that everything is working as it should be, and no part of our ecosystem is relying on AI to function.
Accuracy is our north star. Our users care deeply about precision, and so do we. If the output of an AI process can’t be trusted, then it’s not adding value. Rather, it’s adding more work and anxiety, both of which we know nobody needs.
We’re also aware that AI technology itself is evolving quickly. Just a year ago, companies were charging six-figure contracts for tools that could read and interpret financial documents. Today, we can achieve that same functionality in-house for just a few cents per document. That’s how fast things are changing.
We don’t want to be first for the sake of being first — we want to be right.
Because of that, we’re cautious about chasing the newest AI trend. Our focus is on adopting technology that’s mature enough to deliver real, measurable benefits for our clients.
How we use AI in SumIt’s products
With all of this said, we’re already leveraging AI in meaningful ways across the SumIt platform. Let’s go over a few real ways that we implement an accuracy-first approach to AI.
1. Transaction categorization
One of the best examples is transaction categorization. We’re leveraging state-of-the-art models from OpenAI, hosted on our own infrastructure through Microsoft Azure, to enhance how transactions are automatically categorized when they come through a bank feed.
This happens in a sealed environment, so your data never leaves Microsoft Azure’s infrastructure and is not used to train OpenAI’s models. AI models use anonymized patterns combined with your existing categorizations on SumIt to make intelligent, context-aware suggestions.
This feature is completely opt-in, so users can decide whether to enable it. It’s a great example of how AI can improve speed and accuracy without compromising control or privacy.
2. Onboarding and data migration
We’re also using AI behind the scenes to make onboarding faster and smoother. Traditionally, moving a family office onto a new accounting platform can take months. Our internal onboarding tooling uses AI to ingest charts of accounts, journal entries, and other data, and then automatically consolidate and map them into a single target chart of accounts on SumIt.
This process, which once required extensive manual work, can now be completed in a matter of days. It’s a small but powerful example of how automation can directly improve client experience without sacrificing accuracy. Now, our clients can migrate to our product more quickly than ever and focus their time on the most important parts of their business.
What’s next at SumIt and the future of family offices
Family office technology is at an inflection point. Technology, in many industries, has shifted to become more proactive, with analytics that can predict events like customer behavior or sales data. This aspect of proactive tech is also the direction we see family office tech going.
As families grow more global, structures become more complex. Data volumes multiply, and systems we’ve been used to will no longer be feasible to serve family offices. AI will move to a collaborator role, and the next generation of family members and professionals will expect intelligent systems — technology that can contextualize information and guide decision-making based on given parameters.
In that sense, we’re actively prototyping several new AI-driven features that will expand automation to other well-defined workflows. Here’s what we’re working on:
1. Document input and reconciliation
One project we’re excited about is automating document ingestion — being able to simply drop in a document and have the system automatically reconcile against transactions already booked in the general ledger. This is now technically possible, and we’re working to turn it into a SumIt feature that saves hours of manual work each week.
2. Natural language queries
We’re also exploring how AI can make data more accessible through natural language queries. Imagine being able to type or ask, “Show me expenses over $50,000 in Q2,” and instantly see the results.
Natural language is an intuitive way to interact with complex data that can help everyone in the office, from the CFO to the bookkeeper, get insights faster.
3. Forecasting and predictive tools
Finally, we’re looking at how AI can support forecasting. While predictive accuracy still has its limits, we believe there’s value in developing tools that help family offices think ahead and scenario-plan with greater efficiency. The key, as always, is balancing innovation with realism.
AI as a collaborative partner
AI is moving fast, and so are we — but with intention. Our philosophy is that technology should evolve alongside our clients, which means intentionally listening closely to prioritize features that make the biggest difference in their day-to-day work.
We also see this article as a living reflection of that journey. Our approach to AI will continue to evolve as the technology itself improves, but one thing won’t change is our commitment to accuracy, security, and privacy. People rely on SumIt to manage their most important financial information, and that remains at the forefront of everything we do.
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